OpenCV is an open source computer vision and machine learning software library. Originally developed by Intel, it is now supported by Willow Garage and has over 2,000 algorithms for computer vision and deep learning. OpenCV is cross-platform and available for Windows, Linux, Android, and Mac. It has C++, Python and Java interfaces and supports machine learning algorithms like SVM and neural networks. OpenCV is used widely in applications like face detection, object recognition, gesture recognition, and more.
The passage discusses the importance of summarization in an age of information overload. It notes that with the massive amounts of data available online, being able to quickly understand the key points of lengthy documents, articles, or reports is crucial. The ability to produce clear, concise summaries helps people filter through large amounts of information and identify what is most important or relevant to them.
- The document summarizes a presentation on deep learning and neural networks given by Junya Kaneko of MPS Yokohama.
- It introduces key concepts of deep learning, neural networks, and TensorFlow for deep learning.
- It provides examples of applications of deep learning like in Android OS, Google Photos, Facebook's DeepFace, and self-driving cars.
- The presentation demonstrates how to set up TensorFlow on a virtual machine and build simple neural networks.
11. 画像認識 (Image Recognition)
Recognition:?
The act of accepting that something is true or
important or that it exists
(出典: http://www.merriam-webster.com/)
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物事の真偽や重要性、またはその存在を認める行動
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Image Recognition:
画像や画像中にあるものが
一体何を意味しているかを理解する第32回 (2015/7/24) MPS 定例ミーティング (c) Junya Kaneko